Module E is evaluating hindcasts from the MiKlip decadal prediction system focusing the main pillars: i) generation of observational data sets and their use for an improved validation of hindcasts, ii) hindcast verification, i.e. the development and implementation of procedures for a quantitative estimation of forecast quality, and iii) process-oriented validation to enhance the understanding and thus the credibility of the prediction system and its products.
Working towards an operational system in MiKlip II, an additional focus comes up: the transfer of predictions from the MiKlip system into probabilistic forecast products for users. This implies a) bias correction of predictions taking a model drift and a climate trend into account, b) calibration of probabilistic forecasts to increase reliability, and c) the construction of forecasts for user-relevant quantities and events, such as heat-waves, droughts, storm surges or other kinds of large-scale climate anomalies.
These pillars define five Module E objectives paving the way towards a useroriented operational system:
1. Bias and Drift correction, Calibration
2. User-oriented post-processing
3. Process-oriented validation
4. Generation of data sets
5. Hindcast verification
Titike K. Bahaga | Andreas H. Fink, Peter Knippertz
Roberto Suárez-Moreno | Belén Rodríguez-Fonseca, Jesús A. Barroso, and Andreas H. Fink
Alexander Pasternack | Jonas Bhend, Mark A. Liniger, Henning W. Rust, Wolfgang A. Müller, Uwe Ulbrich
Knippertz, P. | Fink, A. H., Deroubaix, A., Morris, E., Tocquer, F., Evans, M. J., Flamant, C., Gaetani, M., Lavaysse, C., Mari, C., Marsham, J. H., Meynadier, R., Affo-Dogo, A., Bahaga, T., Brosse, F., Deetz, K., Guebsi, R., Latifou, I., Maranan, M., Rosenberg, P. D., and Schlueter, A.
Dietzsch, F. | A. Andersson, M. Ziese, M. Schröder, K. Raykova, K. Schamm, A. Becker
Pattantyús-Ábrahám, M. | C. Kadow, S. Illing, W. Müller, H. Pohlmann, W. Steinbrecht